A global view of severe maternal morbidity: moving beyond maternal mortality
Bibliographic record
Abstract
BACKGROUND: Maternal mortality continues to be of great public health importance, however for each woman who dies as the direct or indirect result of pregnancy, many more women experience life-threatening complications. The global burden of severe maternal morbidity (SMM) is not known, but the World Bank estimates that it is increasing over time. Consistent with rates of maternal mortality, SMM rates are higher in low- and middle-income countries (LMICs) than in high-income countries (HICs). SEVERE MATERNAL MORBIDITY IN HIGH-INCOME COUNTRIES: Since the WHO recommended that HICs with low maternal mortality ratios begin to examine SMM to identify systems failures and intervention priorities, researchers in many HICs have turned their attention to SMM. Where surveillance has been conducted, the most common etiologies of SMM have been major obstetric hemorrhage and hypertensive disorders. Of the countries that have conducted SMM reviews, the most common preventable factors were provider-related, specifically failure to identify "high risk" status, delays in diagnosis, and delays in treatment. SEVERE MATERNAL MORBIDITY IN LOW AND MIDDLE INCOME COUNTRIES: The highest burden of SMM is in Sub-Saharan Africa, where estimates of SMM are as high as 198 per 1000 live births. Hemorrhage and hypertensive disorders are the leading conditions contributing to SMM across all regions. Case reviews are rare, but have revealed patterns of substandard maternal health care and suboptimal use of evidence-based strategies to prevent and treat morbidity. EFFECTS OF SMM ON DELIVERY OUTCOMES AND INFANTS: Severe maternal morbidity not only puts the woman's life at risk, her fetus/neonate may suffer consequences of morbidity and mortality as well. Adverse delivery outcomes occur at a higher frequency among women with SMM. Reducing preventable severe maternal morbidity not only reduces the potential for maternal mortality but also improves the health and well-being of the newborn. CONCLUSION: Increasing global maternal morbidity is a failure to achieve broad public health goals of improved women's and infants' health. It is incumbent upon all countries to implement surveillance initiatives to understand the burden of severe morbidity and to implement review processes for assessing potential preventability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".